Exact two-sample inference with missing data

Biometrics

Volumn 61, Issue 2, 2005, Pages 524-531

  Cheung, Ying Kuen ^a  

^a Columbia University ^*  (United States)

Author keywords

Bootstrap; Covariate dependent dropout; Gibbs sampler; Missingness at random; Permutation; Test inversion; U statistic; Weighting; Wilcoxon test

Indexed keywords

POPULATION STATISTICS;

BOOTSTRAP; COVARIATE-DEPENDENT DROPOUT; COVARIATES; GIBBS SAMPLERS; MISSINGNESS AT RANDOM; PERMUTATION; TEST INVERSION; U-STATISTICS; WEIGHTING; WILCOXON TEST;

MONTE CARLO METHODS;

BOOTSTRAPPING; STATISTICAL ANALYSIS;

ARTICLE; COVARIANCE; DATA ANALYSIS; FOLLOW UP; HYPOTHESIS; MEASUREMENT; MONTE CARLO METHOD; NONPARAMETRIC TEST; PILOT STUDY; POPULATION RESEARCH; PROBABILITY; RANK SUM TEST; SAMPLING;

EID: 20744453505     PISSN: 0006341X     EISSN: None     Source Type: Journal    
DOI: 10.1111/j.1541-0420.2005.00332.x     Document Type: Article

References (17)

1. Beaulieu, C., de Crespingriy, A., Tong, D. C., Moseley, M. E., Albers, G. W., and Marks, M. P. (1999). Longitudinal magnetic resonance imaging study of perfusion and diffusion in stroke: Evolution of lesion volume and correlation with clinical outcome. Annals of Neurology 46, 568-578.
2. Cheung, Y. K. and Klotz, J. H. (1997). The Mann Whitney Wilcoxon distribution using linked lists. Statistica Sinica 7, 805-813.
3. Diggle, P. and Kenward, M. G. (1994). Informative dropout in longitudinal data analysis (with discussion). Applied Statistics 43, 49-94.
4. Fitzmaurice, G. M., Laird, N. M., and Rotnitzky, A. G. (1993) Regression models for discrete longitudinal responses. Statistical Science 8, 284-309.
5. Geman, S. and Geman, D. (1984). Stochastic relaxation. Gibbs distributions and the Bayesian restoration of images. IEEE Transactions of Pattern Analysis and Machine, Intelligence 6, 721-741.
6. Glidden, D. V. and Wei, L. J. (1999). Rank estimation of treatment differencies based on repeated measurements subject to dependent censoring. Journal of the American Statistical Association 94, 888-895.
7. Johnson, N. L., Kotz, S., and Balakrishnan, N. (1997). Discrete Multivariate Distributions. New York: Wiley.
8. Lee, Y. (1997). A two-sample nonparametric test with missing observations. American, Journal of Mathematical and Management Sciences 17, 187-200.
9. Little, R. J. A. (1995). Modeling the drop-out mechanism in repaated-measures studies. Journal of the American Statistical Association 90, 1112-1121.
10. Mehta, C. R., Patel, N. R., and Tsiatis, A. A. (1984). Exact significance testing to establish treatment equivalence with ordered categorical data. Biometrics 40, 819-825.
11. Roberts, GO. (1995). Markov chain concepts related to sampling algorithms. In Markov Chain Monte Carlo in Practice, W. R. Gilks, S. Richardson, and D. J. Spiegelhalter (eds), 45-57. London: Chapman & Hall.
12. Robins, J. M., Rotnitzky, A., and Zhao, L. P. (1995). Analysis of semiparametric regression models for repeated outcomes in the presence of missing data. Journal of the American Statistical Association 90, 106-121.
13. Rubin, D. B. (1976). Inference and missing data. Biometrika 63, 581-592.
14. Wei, L. J and Johnson, W. E. (1985). Combining dependent tests with incomplete repeated measurements. Biometrika, 72, 359-364.
15. Wei, L. J. and Lachin, J. M. (1984). Two-sample asymptotically distribution-free tests for incomplete multivariate observations. Journal of the American Statistical Association 79, 653-661.
16. Wilcoxon, F. (1945). Individual comparisons by ranking methods. Biometrics 1, 80-83.
17. Yao, Q., Wei L. J., and Hogan, J. W. (1998). Analysis of incomplete repeated measurements with dependent, censoring times. Biometrika 85, 139-149.